Contents Index Volume 35 and 36

Active safety systems would benefit from tyre force and friction potential information. Different sensor concepts, including, among others, the EU–funded Apollo–project developed tyre sensor based on optical position detection, are being studied. The sensor can measure tyre carcass deflections with respect to the rim. The carcass deflections can be used to calculate tyre forces and they may be exploited in the estimation of friction potential. The waveforms of the sensor signal are illustrated. The vertical and lateral force estimations are presented with unavoidable compensation parts. The tyre sensor measurements were compared to the measurement–vehicle results and good correlations achieved. Continuing activities are concerned with the estimation of friction potential and the detection of aquaplaning.     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

基于应力松弛试验用有限元预估车辙

为了使车辙预估变得更为简便,提出一种基于应力松弛试验的改进的有限元车辙预估方法。研究结果表明：不仅从粘弹性力学的角度分析,应力松弛试验在理论上与Maxwell模型具有一致性,而且实例计算结果也验证了此方法的可行性。该方法便于不熟悉本构理论的工程人员进行车辙预估。     

基于卡尔曼滤波算法的电机转速精确估计

从无刷直流电机入手建立数学模型，利用卡尔曼Kalman（EKF）滤波原理算法，对无刷直流电机的转速进行精确估计，然后在Matlab环境下仿真，验证卡尔曼滤波算法对电机转速估计的精确性。     

An inverse finite element method for the analysis of VIV data

This paper presents an algorithm for the frequency domain solution of dynamic linear “inverse” problems, that is for the processing of measurement data (strain, acceleration etc.) acquired on a mechanical structure, in order to estimate the loads acting on the structure and its corresponding response. The problem is formulated as a constrained (force equilibrium) optimization (small deviations from measurements, small loads) problem, which is transformed into an unconstrained problem, then into differential equations. The algorithm is applied to the estimation of hydrodynamic forces induced by the shedding of vortices from an offshore oil riser.     

Road roughness estimation based on discrete Kalman filter with unknown input

ABSTRACT

The road roughness acts as a disturbance input to the vehicle dynamics, and causes undesirable vibrations associated with the ride and handing characteristics. Furthermore, the accurate measurement of road roughness plays a key role in better understanding a vehicle dynamic behaviour and active suspension control systems. However, the direct measurement by laser profilometer or other distance sensors are not trivial due to technical and economic issues. This study proposes a new road roughness estimation method by using the discrete Kalman filter with unknown input (DKF-UI). This algorithm is built on a quarter-car model and uses the measurements of the wheel stroke (suspension deflection), and the acceleration of the sprung mass and unsprung mass. The estimation results are compared to the measurements by laser profilometer in-vehicle test.     

基于Monte Carlo抽样方法的随机离散化在分组数据中的应用

对一种基于Monte Carlo抽样方法的随机离散化做了改进,并将改进后方法应用于分组数据的统计推断中,用来计算未知参数的近似极大似然估计和区间估计.改进后的方法弥补了原方法有时不能满足Sn(f)≈S(f)的缺点.该方法思想简单,易于执行,并且是非迭代,任意维的.所以,通过实例模拟,还可以看出该方法运行速度快,远优于Gibbs抽样、EM算法等其它几种方法.而且运算结果精度高,尤其表现在未知参数的区间估计上.因此提供了一种计算未知参数估计的简单方法.     

编组站动态配流模型与算法研究

如何从众多的解体方案中选择有利方案 ,这是编组站动态配流所要解决的核心问题。本文在文献 [3 ]的基础上 ,运用组合数学原理构造方案树 ,提出最大可能剩余量概念 ,导出计算公式 ,并以此作为方案值控制树的生长 ,进而利用回溯算法搜索有利方案。这样 ,本文连同文献 [2 ]、[3 ]一起 ,为配流问题的全面解决提供了完整的思路和具体的计算方法     

基于双目视觉计算的车辆跟驰状态实时感知系统

双目视觉技术能够实现目标的识别与距离计算，在自动驾驶领域有很大的应用空间。然而，现阶段双目视觉存在光照干扰、遮挡、弱纹理区域歧义匹配等问题，影响其测量的准确性和可靠性。提出基于双目视觉的跟驰状态实时感知系统，该系统采用基于车辆跟驰模型的扩展卡尔曼滤波方法对车辆跟驰状态进行实时估计，包括跟驰距离、前后车速度差等。通过实际道路试验，证明了该系统能够识别并修正测量数据中的异常值，解决弱纹理区域误匹配问题。试验结果表明：25 mm焦距与12 mm焦距的双目系统跟驰间距测量值的平均误差分别为2.66%与9.14%；在相对速度测量方面，2种焦距系统的测量精度基本相同，平均误差均为1 m·s^-1左右。所提出的方法在自动驾驶车辆环境感知领域有较好的应用前景。     

铁路枢纽折角车流数值变化的动态模拟

以解编车流作业规则和系统资源限制为约束,构造不同目标函数下铁路枢纽编组站作业分工数学模型,给出折角车流理论最大值和最小值及相应编组站作业分工方式及车流条件。基于折角车流变化的复杂性和多样性,将外部车流环境视为一个动态的随机输入,以特定铁路枢纽为背景用计算机模拟技术和遗传算法计算不同条件下折角车流数值解。通过对模拟数据趋势变化比较分析,提出铁路枢纽运输组织不应过分追求折角车流最小等结论。